Minimalistic control of a compass gait robot in rough terrain

Authors:
Fumiya Iida;Russ Tedrake
Affiliations:
Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, MA;Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, MA
Venue:
ICRA'09 Proceedings of the 2009 IEEE international conference on Robotics and Automation
Year:
2009

Citing 3
Cited 4

Passive dynamic walking

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Applied optimal control for dynamically stable legged locomotion

Applied optimal control for dynamically stable legged locomotion
Swing-Leg Retraction for Limit Cycle Walkers Improves Disturbance Rejection

IEEE Transactions on Robotics

Metastable Walking Machines

International Journal of Robotics Research
Minimalistic control of biped walking in rough terrain

Autonomous Robots
Using efference copy and a forward internal model for adaptive biped walking

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Stable dynamic walking over uneven terrain

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Abstract

Although there has been an increasing interest in dynamic bipedal locomotion for significant improvement of energy efficiency and dexterity of mobile robots in the real world, their locomotion capabilities are still mostly restricted on flat surfaces. The difficulty of dynamic locomotion in rough terrain is mainly originated in the stability and controllability of gait patterns while exploiting the natural mechanical dynamics of the robots. For a systematic investigation of the challenging problem, this paper presents the simplest control architecture for the compass gait model which can be used for locomotion in rough terrain. Locomotion of the model is mainly achieved by an open-loop oscillator which induces self-stabilizing gait patterns, and we test the proposed control architecture in a real-world robotic platform. In addition, we also found that this controller is capable of varying stride length with a minimum change of control parameters, which enables locomotion in rough terrains. By using these basic principles of self-stability and gait variability, we extended the proposed controller with a simple sensory feedback about the location in the environment, which makes the robot possible to control gait patterns autonomously for traversing a rough terrain. We describe a set of experimental results and discuss how the proposed minimalistic control architecture can be enhanced for dynamic locomotion control in more complex environment.